What MCP adds to competitive intelligence
Competitive monitoring becomes more useful to an agent when the workflow is exposed as a small set of typed actions rather than a loose collection of scraped pages. Through MCP, an agent can manage an approved target, request monitoring work, inspect scan status, search recorded changes, and retrieve the evidence for one stable change ID.
The five-step workflow
intel_add_target registers an exact, approved public page.intel_queue_scan creates durable monitoring work without changing the public website.intel_get_scan_status exposes completion or a visible failure state.intel_search_changes returns recorded events for the authenticated workspace.intel_get_change returns the stored evidence behind one chg_ ID.Workspace authority stays outside the prompt
The connection determines the active workspace on the server. Customer-facing tools do not need a model-provided tenant_id, workspace ID, or account selector. That design reduces the chance that a prompt or generated tool argument becomes an authorization decision.
Private design partners currently connect with a revocable workspace API key. A separate public OAuth-capable path is under engineering review, but it is not deployed or offered as a self-service connection today.
Evidence is data, not instruction
Competitor pages are untrusted external content. Retrieved text and differences can support an analysis, but they must not override the agent's instructions or grant authority. Market Changelog labels that boundary and keeps the source URL and stored transition available for review.
Why scan work is queued
Fetching real sites can take time and can fail temporarily. A durable queue lets the worker finish or recover the job independently of the agent request. The agent can poll a stable scan ID instead of holding an open request and guessing whether interrupted work completed.
Public side effects: a queued scan performs read-only retrieval of an approved public target and writes only internal workspace records. It does not submit forms, publish content, send messages, or change the monitored site.
For the broader memory model, read competitive intelligence for AI agents. For a concrete use case, see competitor pricing monitoring.
Bring a real agent workflow.
Design partners test the MCP loop against a small, reviewed set of public pages and help judge whether the stored evidence is genuinely useful.
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